Book Image

Practical Data Wrangling

By : Allan Visochek
Book Image

Practical Data Wrangling

By: Allan Visochek

Overview of this book

Around 80% of time in data analysis is spent on cleaning and preparing data for analysis. This is, however, an important task, and is a prerequisite to the rest of the data analysis workflow, including visualization, analysis and reporting. Python and R are considered a popular choice of tool for data analysis, and have packages that can be best used to manipulate different kinds of data, as per your requirements. This book will show you the different data wrangling techniques, and how you can leverage the power of Python and R packages to implement them. You’ll start by understanding the data wrangling process and get a solid foundation to work with different types of data. You’ll work with different data structures and acquire and parse data from various locations. You’ll also see how to reshape the layout of data and manipulate, summarize, and join data sets. Finally, we conclude with a quick primer on accessing and processing data from databases, conducting data exploration, and storing and retrieving data quickly using databases. The book includes practical examples on each of these points using simple and real-world data sets to give you an easier understanding. By the end of the book, you’ll have a thorough understanding of all the data wrangling concepts and how to implement them in the best possible way.
Table of Contents (16 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback

Using the pandas module to read and process data

Pandas is a set of tools for easy manipulation and analysis of tabular data. Among these tools is an object for representing and manipulating tabular data called a dataframe. With a dataframe, it is possible to express row-wise and column-wise operations to be performed on the data. Pandas can simplify the process of working with data considerably, requiring fewer lines of code and making the process more intuitive.

Counting the total road length in 2011 revisited

In this next demonstration, you will approach the same problem of enumerating the road length--this time using pandas. To start off with, create a file called that import the pandas module as follows:

import pandas

Reading CSV data using the pandas module is quite simple. Pandas combines the process of opening a file with the process of reading and parsing the data. To read a CSV file using the pandas module, you can use the pandas.read_csv() function. The pandas.read_csv...